Wind-induced variability in the Northern Current (northwestern Mediterranean Sea) as depicted by a multi-platform observing system

Wind-induced variability in the Northern Current (northwestern Mediterranean Sea) as depicted by...

Wind-induced variability in the Northern Current (northwestern Mediterranean Sea) as depicted by a multi-platform observing systemWind-induced variability in the Northern Current (northwestern Mediterranean Sea) as depicted by...Maristella Berta et al.

The variability and evolution of the Northern Current (NC) in the area off
Toulon is studied for 2 weeks in December 2011 using data from a glider, a
high-frequency (HF) radar network, vessel surveys, a weather station, and an atmospheric model.
The NC variability is dominated by a synoptic response to wind events, even
though the dataset also evidences early stages of transition from late summer
to fall–winter conditions. With weak winds, the current is mostly zonal and
in geostrophic balance even at the surface, with a zonal transport associated
with the NC of ≈1 Sv. Strong westerly wind events (longer than
2–3 days) induce an interplay between the direct-wind-induced ageostrophic
response and the geostrophic component: upwelling is observed, with offshore
surface transport, surface cooling, flattening of the isopycnals, and reduced
zonal geostrophic transport (0.5–0.7 Sv). The sea surface response to wind
events, as observed by the HF radar, shows total currents rotated at ≈-55 to -90∘ to the right of the wind. Performing a
decomposition between geostrophic and ageostrophic components of the surface
currents, the wind-driven ageostrophic component is found to rotate by
≈-25 to -30∘ to the right of the wind. The ageostrophic
component magnitude corresponds to ≈2 % of the wind speed.

The Liguro–Provençal–Catalan Current, also called Northern Current
(Millot, 1999), is a boundary current corresponding to the upper limb of
the western Mediterranean circulation (Fig. 1a). It originates in the
Ligurian Sea due to the convergence of the two currents flowing along each
side of the Corsica island (Astraldi and Gasparini, 1992), namely the Western and
Eastern Corsica currents (WCC and ECC). The Northern Current (denoted NC
hereafter) flows southwestward along the continental slope of the
Ligurian–Provençal and Balearic basins with a certain degree of
continuity and may thus be recognized as a single entity as far as the
Catalan Sea (Font et al., 1988; Garcia et al., 1994; Millot, 1987). Its importance mainly
relies on the fact that all water masses in the area – namely the Modified
Atlantic Water (MAW), the Levantine Intermediate Water (LIW) and the Western
Mediterranean Deep Water (WMDW) – are carried by the current during its
flowing (Conan and Millot, 1995). As a result, the NC is known to influence the
coastal circulation of the Gulf of Lion (Duchez et al., 2012) and, most
importantly, to modulate the supply of salt and/or heat by lateral advection
in the convection areas (so-called preconditioning; see
Schroeder et al., 2010) and thus to affect the important deep water
formation process in the western Mediterranean. Also, the NC hugs the highly
populated coasts of Italy and France, where areas of intense industrial
development alternate with touristic and environmental relevant marine
protected areas (MPAs). Understanding the flow dynamics and how it carries
biological and pollutant quantities is of great importance for a correct
management of coastal and marine activities.

Figure 1(a) The western Mediterranean Sea, including northern
circulation branches and main winds. The region of study is marked as a
dashed black square. The following acronyms are used: GoL: Gulf of Lion, NC:
Northern Current, WCC: Western Corsica Current, ECC: Eastern Corsica Current.
(b) Details of the region of study including the synoptic
measurements carried out during the experiment (2–19 December 2011). The
gray area is the high-frequency (HF) radar surface current field coverage,
while the two red crosses indicate the HF radar sites at Fort Peyras (FP) and
Cap Bénat (CB), in the Toulon (TLN) area. The orange square marks represent
the conductivity–temperature–depth (CTD) stations, while the dot array at
6.20∘ E shows the track of the repeated glider transects. CTD
stations and glider tracks are color coded in time. The blue diamond
indicates Porquerolles weather station's position. Bathymetric lines are at 500, 1000 and 2000 m depths.

Despite the numerous articles above, the study of the NC and its variability
still represents an active area of research, especially at scales shorter
than seasonal. Transport measurements provide a wide range of values in the
literature, reaching minimum values of 0.5 Sv and showing significant
variability in time (Conan and Millot, 1995) and in space (Petrenko, 2003). The
reason for this variability within the annual cycle is not clear yet. It has
been suggested that it may be due to different freshwater signals from
precipitation and river runoff (Béthoux et al., 1988), to the WMDW formation
process (Crépon and Boukthir, 1987), or inherited by the distinct behavior of the WCC
and the ECC, whose annual peaks differ by several months
(Astraldi and Gasparini, 1992).

In particular, the study of variability of the NC in the area off Toulon
(between Nice and Marseilles) deserves particular attention for various
reasons. The NC dynamics has been undersampled in the past and far less
documented than in other regions such as off Nice and Marseille. Only
recently the NC mesoscale meandering off Toulon has been specifically
investigated through the comparison of models and observations
(Guihou et al., 2013) and with data assimilation (Marmain et al., 2014). These
studies indicate the role of prevailing northwesterly winds in the modulation
of the NC circulation. In fact, the area near Toulon is peculiar because the
mean NC circulation is resisted by the prevailing northwesterly winds in the
area. The upwelling-prone winds can significantly alter the current, to the
point that on some occasions they can stop its westward propagation and
control its penetration in the Gulf of Lion (Millot and Wald, 1980). When this
happens, a frontal zone separating warm NC waters and cold waters upwelled
from the Gulf of Lion is established near the coast, and it has clearly been
observed from satellite images (Millot and Wald, 1980).

In this paper, the variability of the NC in the area off Toulon is studied
using results from a multi-platform experiment involving high-frequency (HF)
radar, glider, a weather station, and a research vessel, carried out in the framework of the EU-MED
project TOSCA (Tracking Oil Spills and Coastal Awareness network,
http://www.tosca-med.eu, last access: 20 July 2018). The experiment
took place during a period of approximately 2 weeks in December 2011
(2–19 December), characterized by intense westerly and northwesterly wind
events. The wind response of coastal boundary currents such as the NC is
complex, and based on the interplay between the direct ageostrophic response
in the surface layers and the geostrophic modifications occurring along the
whole water column. The response of boundary currents to winds has been
studied by several authors using numerical model results, satellite, and in
situ data (Aguiar et al., 2014; Magaldi et al., 2010; Schaeffer and Roughan, 2015). Experimental works
are mostly based on a statistical approach, i.e., using long time series of
wind and currents and computing correlations or identifying the main flow
patterns corresponding to specific wind forcing (Kim et al., 2010; Kosro, 2005; Mihanović et al., 2011; Yuan et al., 2017).

Here, we focus on the dynamics of specific wind events, and take advantage of
the multi-platform information, especially from HF radars for the surface and
glider for the water column. Our general goal is to identify the main
processes at work, and to investigate how to unravel the interplay between
the direct-wind-induced surface response and the geostrophic response. The
following two specific goals are pursued:

describing the sea current system evolution during the period of
interest, quantifying the water column response to the wind in terms of
isopycnal and zonal geostrophic velocity evolution; and

investigating the surface layer response to the wind, attempting a
decomposition between geostrophic and ageostrophic components of the
velocity.

The problem of decomposing the surface flow in geostrophic and ageostrophic
components has been previously addressed in several works. Earlier works used
hydrographic or acoustic Doppler current profiler (ADCP) information to infer the geostrophic flow
(e.g., Chereskin and Roemmich, 1991; Weller et al., 1991; Wijffels et al., 1994), while more recently the
global altimetric products (Lagerloef et al., 1999) have been used in several
applications. Rio and Hernandez (2003) used Surface Velocity Program (SVP) drifters and altimetry to infer
information at global scales, while HF radar results with altimetry have been
used to compute wind-driven velocities in the Kuroshio Current
(Tokeshi et al., 2007) and in the South Atlantic Bight (Yuan et al., 2017).
However, for coastal boundary currents such as the NC and for the space and
timescales we are interested in (tens of kilometers and days), the use of
satellite altimetry requires special attention (Gómez-Enri et al., 2016; Vignudelli et al., 2000) and is often not appropriate because of problems of accuracy, land
contamination, and low space and time resolution at least for global products
(Berta et al., 2015; Bouffard et al., 2008).

In this paper, we investigate the use of glider data in conjunction with HF
radar. There are several challenges in using glider transects, including
limited space and time sampling (Piterbarg et al., 2014) and the fact that only
one component of the geostrophic velocity can be retrieved. Here, we
investigate how to best combine glider and HF radar data and in which flow
conditions they can be best exploited.

The paper is organized as follows. In Sect. 2, the main questions addressed
in the paper are stated, and the main definitions are introduced. In
Sect. 3, a description of the data as well as the methods used to analyze
them is provided. In Sect. 4, a description of the sea current system
evolution over the whole water column is provided, while the analysis of the
wind response in the surface layer is performed in Sect. 5. A summary and
discussion are provided in Sect. 6.

As stated in the introduction, the general goal of this work is to
investigate the variability of the NC during the period of interest, with
special focus on the response of the system to wind forcing, using
information from glider and HF radar. The velocity field of the system
u(x,y,z,t) can always be written through kinematic decomposition as
the superposition of a geostrophic and an ageostrophic component:

(1)u=ug+ua.

The geostrophic part, ug, obeys the balance between
pressure gradient and Earth rotation (Coriolis). In the case of a boundary
current, ug is expected to be driven by the large-scale
pressure gradient of the general circulation, as well as by the more
localized pressure gradient of mesoscale phenomena such as meanders and
eddies (Centurioni et al., 2008; Gangopadhyay et al., 2013). The ageostrophic component,
ua, includes the phenomena that are not in geostrophic
balance. In the water column interior, we can expect that the flow is mostly
geostrophic at scales longer than a day, while high-frequency processes such
as internal waves, tides, or inertial oscillations play an important role at
shorter timescales (Mensa et al., 2013).

At the surface, in
addition to high-frequency processes, also ageostrophic processes related to
direct wind and air–sea interaction are relevant. In particular, the surface
velocity uS(x,y,t) can be written as

(2)uS=uSg+uSaW+uSR,

where uSg is the surface geostrophic velocity,
uSaW is the directly wind-driven component, and
uSR includes all the other high-frequency processes such as
tides, inertial and submesoscale variability, that for the purpose of this
paper we will refer to as “residual”.

The wind response uSaW has been studied for many decades,
starting from the pioneering work by Ekman (1905), considering idealized
solutions of the balance between Coriolis and friction. The classic Ekman
solution, valid in stationary and homogeneous conditions of infinite domain
in the horizontal and at depth, is characterized by a surface current at
45∘ to the right of the wind (in the Northern Hemisphere) spiraling
with depth in the surface layer. The solution is highly dependent on the
specific parameterization of wind stress and vertical diffusivity. As an
example, assuming that the wind stress linearly decreases with depth, this leads
to the “slab” solution, which is 90∘ to the right of the wind and
constant with depth (Pollard and Millard, 1970). The choice of other
parameterizations as well as the presence of boundaries, finite depth, time
dependence, and inhomogeneity further modifies the solution (Crise et al., 2006; Endoh and Nitta, 1971; Ralph and Niiler, 1999). Also, it can be expected that the simplified balance
of the Ekman equation only partially captures the dynamics in realistic
conditions, because of the interactions between the various processes.
Indeed, direct measurements show a great range of variability in the observed
wind response (Rio and Hernandez, 2003; Sentchev et al., 2017). In summary, even though the
idealized solutions provide very important general guidance, the actual
surface response to the wind in realistic conditions is still an open
question (Stanichny et al., 2016), and it can be expected to depend on the
specific environmental conditions.

We notice that there is a well-known direct dynamical link between
uSaW and the geostrophic velocity ug. In
the case of a boundary current, when the wind induces cross-shore transport,
the cross-shore pressure gradient can be modified provided that the wind acts
for a sufficiently long timescale, TW(Whitney and Garvine, 2005). For
the Northern Current, Piterbarg et al. (2014) estimated that for winds of the
order of 10 m s−1TW is of the order of 2.5–3 days. In
the case of upwelling-prone winds, as is the case of the westerly winds
considered here, the ageostrophic surface response causes offshore transport
that is compensated by deep water coastal upwelling, modifying both the
surface pressure gradient and the water column stratification estimated by
the potential density anomaly σ(z). This, in turn, alters the
along-shore geostrophic component of the flow. In addition to this main
mechanism, the geostrophic response can be further modulated by several other
mechanisms, such as nonlinear frontal wind response (Oguz et al., 2017), and
interactions with mesoscale and submesoscale instabilities.

The work performed here has two specific goals:

The first goal is to describe the variability of the NC over the whole water column and
investigate its relationship with wind forcing.

The full 3-D description of u(x,y,z,t) is clearly not available from
our data, but the data from glider and HF radar provide a good first
approximation of the sea current system. The radar data provide estimates of
the 2-D surface velocities u(x,y,t), while the glider data provide
information on the interior flow in terms of stratification, σ(y,z,t),
and zonal geostrophic velocity, ug(y,z,t), estimated along the
cross-shore glider transect. In this part of the work, we concentrate on
variability over timescales of 1 day or longer, in keeping with the use of
glider transect data and geostrophic velocities. In particular, we
investigate the response of the sea current system during intense westerly
wind events and concentrate on the main mechanism between wind-induced
surface transport and upwelling response. Other mechanisms such as nonlinear
wind response and interaction with instabilities are not directly considered
here because we do not have enough information to resolve the various
aspects.

The second goal is to further investigate the wind response in the surface layer and test a
method to estimate the induced ageostrophic component uSaW.

The high-frequency response of the surface velocity uS(x,y,t) as provided by the radar is used as a basis for
the analysis. The estimate of uSaW is performed during
periods of high winds, when it can be assumed that this term is prevalent
with respect to uSR in Eq. (2). Still, the difficulty lies
in identifying a reliable estimate for uSg(x,y,t) to be
subtracted from uS(x,y,t) in Eq. (2). A simple method
based on the combined analysis of glider and HF radar data is put forth,
valid for specific dynamic regimes.

Here, we review the datasets used in this study and describe the main data
treatments and analyses that have been carried out. The data spatial coverage
is shown in Fig. 1b, while a timeline of the measurements is shown in
Fig. 2a.

Figure 2(a) The multi-platform observations timeline: the black
dashed lines indicate the selected wind events (compare with the panel
below), the gray area indicates the radar dataset availability, the red areas
indicate the glider transects, and the green dashed lines indicate the period
in which the glider transects fall inside the HF radar coverage.
(b) Wind time series from Porquerolles weather
station (blue line) and from the
ALADIN model (black line) are compared in terms of speed (middle panel) and
direction (bottom panel). The limits of the selected wind events
(speed >10 m s−1, gray line in the middle panel) are indicated with
red dashed lines and named E1, E2, and E3.

3.1 Vessel-based measurements

During the experimental effort, an oceanographic cruise took place aboard the
Italian R/V Urania between 10 and 15 December 2011. While
measurements were performed within an extended offshore area between Nice and
Toulon, here we consider only the Toulon measurements taken on 13 and
14 December. A total of 11 conductivity–temperature–depth (CTD) stations were sampled in the surrounding of
the glider transect (Fig. 1b). The CTD data have been used for
intercomparison and calibration of the glider hydrographic data as further
discussed in Sect. 3.2–3.3.

3.2 Gliders

An autonomous underwater glider of the Slocum kind (Jones et al., 2005),
manufactured by Webb Research Corporation, has been deployed and maintained
operational during the period of 2–19 December (Fig. 2a). The glider, named
Hannon, covered six repeated meridional transects off Toulon extending
∼70 km offshore (Fig. 1b). The onshore half of the transects laid
within the HF radar coverage. The maximum profiling depth was set to 1000 m,
giving mean horizontal distance between consecutive profiles, mean horizontal
speed, and mean vertical speed of 1.7 km, 35 cm s−1, and
20 cm s−1, respectively. The timing details of each transect are
summarized in the timeline in Fig. 2a and in Table 1.

Hannon was equipped with an unpumped SBE 41 CTD manufactured by Sea-Bird
Electronics. CTD data were processed with dedicated Matlab routines taking
care of all classic CTD response times and alignment issues, and all
parameters were rebinned onto a regular vertical grid with a step of 2 dbar.
Due to the use of an unpumped CTD and to the variable speed of the autonomous
vehicle, the corrections were made speed-dependent using the glider speed
computed through pressure variations and tilt angle. The thermal lag of the
conductivity sensor was dealt also with speed-dependent coefficients
(Morison et al., 1994) experimentally found through the technique proposed by
Garau et al. (2011). The optimum values of the coefficients were
αo=0.5447, αs=0.0708, τo=9.5117, and τs=7.69. Finally, temperature and
conductivity values were post-calibrated against the Sea-Bird Electronics SBE
911+ CTD deployed from the R/V. For this purpose, only glider and ship
profiles distant less than 14 km and separated by less than 12 h were
considered, discarding all data shallower than 600 dbar.

The glider hydrographic data were used to describe the NC current
stratification and evolution. The hydrographic glider data have also been
used to compute relative geostrophic velocities in the direction
perpendicular to the glider transects, corresponding to the zonal direction.
Potential density profiles were used, previously low-pass filtered through a
Gaussian filter with 9 km cut-off wavelength. The Rossby radius was found
through the dynamic mode decomposition of the average Brunt–Väisäla
frequency profiles (Kundu et al., 1975). Although depth-averaged velocities from
the glider could have been used to reference the geostrophic velocities, as
done, e.g., by Davis et al. (2008), a calibration problem in Hannon's magnetic
compass prevented us from doing so. Therefore, the velocities were referenced
to a level of no motion z0, assumed to be in the range between
500–700 m. Sensitivity tests on z0 between 500 and 700 show very limited
variability, with root mean square differences in the mean upper layer
velocity of ≈2 %. In the following, results with z0=500 m are
used.

The zonal geostrophic velocities were used also to compute the integrated
transport, using the 5 cm s−1 isotach to identify the Northern
Current, as done, e.g., by Albérola et al. (1995a) and Conan and Millot (1995).

3.4 HF radar

The HF radar (HFR) system has been operational during the period 6–19 December
(Fig. 2a), covering the area in front of Toulon (Fig. 1b). The HF radar
installation is based on the WERA technology (Gurgel et al., 1999) and relies on
two systems. The first one (Fort Peyras, “FP” in Fig. 1b) has a
quasi-monostatic configuration with an irregular, W-shaped eight-antenna
receiving array and two monopoles performing the emission while forming a zero
in the direction of the receiver. The peculiarity of the receiving array
geometry is imposed by the environment of the site, a dismissed military
base. The second system (Cap Bénat, “CB” in Fig. 1b) has a fully
bistatic configuration, with the two monopoles in FP employed as emitter, and a
regular linear eight-antenna array in CB operated as receiver (transmitter and
receiver are 35 km apart).

The two systems operate at a frequency of 16.1 MHz with 50 kHz bandwidth,
giving a nominal range resolution in the radial direction of 3 km. Antenna
patterns are routinely measured almost every year and they had been applied
to the December 2011 dataset. The azimuthal processing is done with the MUSIC
(MUltiple SIgnal Characterization) direction-finding algorithm with a nominal 2∘ spacing
(Lipa et al., 2006; Molcard et al., 2009; Sentchev et al., 2013), and radial velocity maps are
produced every 20 min by integrating over the previous hour. Total velocity
maps are then obtained on a regular 2 km grid through a local interpolation
method which, at each grid point, minimizes the mean square error (MSE)
between the projection of the total velocity onto the radial directions and
the radial velocities available within a 3 km radius circle
(Lipa and Barrick, 1983). Classically, total velocities are only computed when the
angle between radial data from the two systems lies within the range
30–150∘, which corresponds to geometric dilution of precision
(GDOP) values smaller than 2.5 (Chapman et al., 1997).

In our case, the requirement on the angle had to be reduced to
20–160∘ (corresponding approximately to GDOP values smaller than 4)
in order to keep an acceptable offshore coverage on the region for the
bistatic configuration. The Toulon radar system has been validated also
during other TOSCA experiments involving the deployment of drifters, used to
compare HF radar fields and derived velocities from in situ trajectories.
Results show a high level of accuracy, on average 80 % agreement between
drifters and HF radar, consistently using FP as quasi-monostatic
configuration, CB as a different bistatic configuration (with emitter in Porquerolles, so that transmitter and receiver are 16 km
apart), and GDOP values smaller than
2.5 (Bellomo et al., 2015; Berta et al., 2014).

HFR-measured velocities are the results of a vertical integration,
through an exponential weighting function, over a characteristic depth
λ0∕4π(Stewart and Joy, 1974), where λ0 is the resonant Bragg
wavelength, which is half the wavelength of the emitted electromagnetic wave.
For our systems, operating at a central frequency of 16.1 MHz, the
characteristic depth is about 75 cm.

Due to the proximity of the FP site emitter with respect to the receiver
array, imposed once again by the constraints of the military base, the HF
radar coverage systematically experienced a drastic loss under strong Mistral
winds. In fact, the wind-induced vibrations of the emitter antennas generated
a phase noise in the receiver antennas' frequency spectrum, making in turn the
signal-to-noise ratio unacceptably low at usually well-covered distances.
Unfortunately, the problem was solved only after the observational campaign
by placing the emitter farther outside the military base.

3.5 Analysis and interpretation of HF radar data

The HF radar fields are used to describe the evolution of the surface
velocities. Preliminary tests have been performed using the raw data as well
as low-pass-filtered data with a cut-off period of 36 h. Results, using raw
and filtered data, agree within 86 % to 99 % in terms of average and rms
velocities for v and u components, respectively, so that only results based
on raw data are presented in the following.

We point out an important general issue regarding the interpretation of
results based on HF radar velocities. Several papers (Ardhuin et al., 2009; Essen, 1993; Mao and Heron, 2008) have pointed out that the HFR-based surface
velocity has, in addition to the actual Eulerian velocity u(x,y,t),
also a nonlinear wave correction (Weber and Barrick, 1977) that can be interpreted as
a filtered surface Stokes drift, including the contribution of waves with
wavelengths longer than the Bragg resonant wavelength.

A method to estimate this term has been proposed based on an accurate
numerical wave model (Ardhuin et al., 2009). A debate is ongoing in the
literature regarding the magnitude of the term and whether it is significant or
not (Mao and Heron, 2008; Röhrs et al., 2015). An important factor is the fetch, since the
longer the fetch, the more important the contribution of long waves
(Essen et al., 2000). In our case, the Bragg resonant wavelength for our system
is approximately 9 m, and the Stokes-like term cannot be explicitly
estimated following Ardhuin et al. (2009) because we do not have access to the
full wave spectrum information for the period of interest. Since the wind is
predominantly from the west and northwest, and given the geography of the
region (Fig. 1a), we can expect that the fetch is limited, and therefore the
term is unlikely to be relevant. In absence of a quantitative estimate,
though, we caution that the wind response term uSaW for our
measurement could include not only the Ekman-type Eulerian response but also
a possible Lagrangian contribution from Stokes drift. We will come back to
this point in Sect. 5.

3.6 Wind data from weather station and atmospheric model

Hourly wind speed and direction measurements have been provided for the
complete period of 2–19 December by Météo-France's Porquerolles
station whose location is shown in Fig. 1b. In addition, Météo-France's
ALADIN operational regional model (1/10∘ and 3 h space and time
resolution, respectively) has also been used.

Time series of wind speed and direction from the Météo-France station and from the
model averaged over the area of interest (Fig. 1b) are shown in Fig. 2b. The
results are qualitatively very similar, showing the good agreement of the
model with the data and indicating that the wind patterns in the area are not
characterized by strong gradients during the period of interest. Only during
the last few days, after 18 December, the two time series show significant
differences.

From the wind time series, events of high wind speed have been identified,
considering a threshold of 10 m s−1. This choice is consistent with
Mistral observations in the Toulon area, such as Caccia et al. (2004) and
Guénard et al. (2005), and it is confirmed a posteriori by the consistency of
the results as discussed in Sect. 5. As shown in Fig. 2a–b, the period
of interest is characterized by two main events that last more than 3 days,
E1 and E3, and a shorter event lasting less than 1 day, E2. The main wind
direction is westerly and northwesterly, compatible with Mistral events in
the area. We notice that E1 and E3 have duration longer than the estimated
value of TW in the area (2–3 days) and therefore are likely to
influence stratification and geostrophic velocity in the NC, as discussed in
Sect. 2. The opposite holds for E2.

3.7 Summary of the measurements

In summary, the timeline of the main measurements carried out during the
experiment is provided in Fig. 2a and includes

glider measurements (red boxes) covering the period of 2–19 December
for a total of six transects, alternating offshore and inshore routes;

HF radar measurements (solid gray) starting 6 December, so that the first glider
transect does not have contemporary HF radar data (the periods in which the glider transects fall inside the radar coverage are shown by green dashed
lines); and

wind measurements and model outputs, which are available during the whole period of 2–19 December (the wind events E1, E2, and E3 are shown as dashed black lines).

4 Water column stratification and geostrophic variability, and effects of wind forcing

In the following, the variability of the Northern Current is described during
the period of interest (2–19 December). For simplicity, we partition the time
of the analyses following the same time intervals as for the glider transects
(Table 1, Fig. 2a). For each transect period, we provide a basic description
based on the wind evolution together with the glider results on hydrography
and zonal geostrophic velocity, and (when available) on the time-averaged
surface velocity fields from HF radar. Radar velocity field averages are
computed during periods in which the glider transects fall inside the radar
coverage and considering only grid points with more than 80 % measurement
coverage in time, in order to avoid mean flow contamination due to
inhomogeneous coverages. For selected transects, all the information above
from glider and HF radar is shown grouped together in a single multi-panel
figure (Figs. 3–6).

Figure 4Potential temperature (a), salinity (b), and
geostrophic velocity (c) for glider Transect 3 (see also Table 1 for
time period definition). Potential density anomaly isolines (black) are in panels
(a) and (b). The black dashed line (c)
represents the southern boundary of the HF radar field. In
panel (d), black arrows show the surface currents from HFR
averaged during the period in which the glider transect (green dashed line)
falls inside the HFR coverage (and considering only grid points with at least
80 % available data over the time period). The blue arrow represents the
wind from Porquerolles station averaged over the same period considered for
the HFR average.

Figure 5Potential temperature (a), salinity (b), and
geostrophic velocity (c) for glider Transect 5 (see also Table 1 for
time period definition). Potential density anomaly isolines (black) are in panels
(a) and (b). The black dashed line (c)
represents the southern boundary of the HF radar field. In panel
(d), black arrows show the surface currents from HFR averaged
during the period in which the glider transect (green dashed line) falls
inside the HFR coverage (and considering only grid points with at least
80 % available data over the time period). The blue arrow represents the
wind from Porquerolles station averaged over the same period considered for
the HFR average.

Figure 6Potential temperature (a), salinity (b), and
geostrophic velocity (c) for glider Transect 6 (see also Table 1 for
time period definition). Potential density anomaly isolines (black) are in panels
(a) and (b). The black dashed line (c)
represents the southern boundary of the HF radar field. In panel
(d), black arrows show the surface currents from HFR averaged
during the period in which the glider transect (green dashed line) falls
inside the HFR coverage (and considering only grid points with at least
80 % available data over the time period). The blue arrow represents the
wind from Porquerolles station averaged over the same period considered for
the HFR average.

In order to quantify the flow variability, we show also some comprehensive
figures that compare all transects in terms of the following metrics:
evolution of the isopycnals σ(z) (Fig. 7), zonal geostrophic transport
(Fig. 8), and comparison between surface zonal geostrophic velocity
uSg estimated from the glider data and total surface velocity
uS considering HF radar data along the glider tracks
(Fig. 9).

During Transect 1 (2–4 December), the glider moves offshore from the coast,
and no HF radar data are available (see Fig. 2a). The wind speed (Fig. 2b) is
initially weak, and then the first westerly event (E1) starts on 3 December.
Notice that the period before the experiment (not shown) was characterized by
calm conditions, with a week of weak winds, with speed smaller than
7.5 m s−1.

The hydrographic properties (potential temperature θ and practical
salinity S) of Transect 1 are shown in Fig. 3a, b for the first 300 m,
with overlying isolines of potential density anomaly σ(z). The
transect plot origin of all hydrographic panels shown in the following
figures is located a few kilometers off the coast (starting point of the
glider mission). Following Boucher et al. (1987), we refer to the three zones
that can be typically distinguished in the NC structure on the basis of the
shape of the isopycnals with potential density anomaly σ in the range
28.7–29.05 kg m−3: the inshore flat part of the isopycnals defines
the “coastal” (or marginal) zone, the sloping part identifies the
“frontal” zone where the NC is most energetic, and the flat offshore part
denotes the “central” basin zone. Here, we use σ=28.7 kg m−3
to characterize these zones (see also Fig. 7). The coastal marginal zone
(typically flat) is not visible in the glider transect, while the frontal
zone is evident and it extends up to ≈42.5∘ N, i.e., at
≈40–45 km offshore. The θ and S transects (Fig. 3a, b)
show a strong thermocline at 50 m in the offshore central region,
accompanied by a salinity minimum (S<38 psu) right below the thermocline
in the frontal zone. The fresher water centered around 80 m depth represents
the core of the Modified Atlantic Water in the shallowest layer, laying over
the Levantine Intermediate Water centered around a core with the highest
salinity values (S>38.55 psu) and a relative temperature maximum. The
presence of stratification with a strong thermocline at 50–100 m, together
with the salinity minimum right below it, is typical of late summer
conditions (Guibout, 1987, pp. 16 and 18 off Toulon and p. 36 off
Nice, Albérola et al., 1995a) still present at the beginning of the
experiment. The zonal geostrophic velocity ug computed along
the transect shows a westward current extending up to 60 km off the coast
with core (up to 0.4 m s−1 in first 100 m) located at
∼42.7–42.8∘ N (Fig. 3c). The offshore limit and depth of
the NC are approximately ∼55 km and ∼175 m, respectively, with
the core situated roughly at 25 km (Albérola et al., 1995a; Petrenko, 2003). The
relatively large width and shallowness of the observed current here, known to
be narrower and deeper than this during winter (Albérola et al., 1995a), confirm
the presence of late-summer conditions at the beginning of the experiment.

4.2 Transects 2–3: wind event E1

During Transects 2 and 3 (4–7 and 7–9 December,
respectively), while the glider travels back inshore and then offshore again,
the wind is mostly dominated by the westerly event E1 (Fig. 2b), tapering off
toward the end of the period. HF radar data are available starting from
6 December (Fig. 2a). The results of the two transects are qualitatively
similar, so the complete results are shown only for Transect 3 in Fig. 4.

The hydrographic transects from the glider show a significant change with
respect to Transect 1 (Fig. 3). Surface waters in the frontal zone are
colder by ≈1.5∘C and the shape of the isopycnals is
significantly flattened, while the mixed layer in the offshore central part
is deepened by ≈20–30 m. This can be seen clearly also in
Fig. 7, where the isopycnal with σ=28.7 kg m−3 is shown for all
transects. Transects 2 and 3 show very similar isopycnal shape in the frontal
area, flatter and shallower than for Transect 1. In the offshore central
region, on the other hand, the isopycnal of Transect 2 is similar to the one
of Transect 1, while for Transect 3 it deepens by ≈20–30 m.
This is likely due to the different sampling times, since the glider covers
the offshore region in Transect 3 about 2 days later than for Transect 2,
and Transect 2 itself takes place shortly after the onset of E1 wind event
(Fig. 2a).

The average surface velocity uS depicted by the HF radar
during the glider sampling (Fig. 2a) is shown in Fig. 4d. Notice the reduced
coverage with respect to the expected coverage (Fig. 1b), due to wind-induced
interferences as discussed in Sect. 3.4. The velocity shows an overall
offshore transport, with localized eastward reversals of the zonal current in
the northwestern part of the radar coverage. The prevalent offshore current
is consistent with the expected wind-driven transport to the right of the
prevalent westerly wind (more in depth discussion is provided in Sect. 5).

Overall, the results suggest the presence of an upwelling phenomenon
associated with the offshore transport induced by the westerly winds, that
causes the flattening of the isopycnals in the frontal region and the cooling
at the sea surface. In addition to the upwelling, other phenomena related to
wind response are likely to occur, as suggested by the offshore isopycnal
deepening in Figs. 4 and 7, due to mixing that deepens the thermocline and
possibly to convection processes. Within the first 50–60 m depth of the
zonal geostrophic velocity transect from the glider (Fig. 4c), we also observe
recirculating cells further offshore the NC front associated with the
wind-driven modification of the water masses' circulation offshore Toulon.
This behavior is analogous to NC variability and meanders observations off
Nice in fall–winter by Albérola et al. (1995a); Sammari et al. (1995). The recirculating
cells are not visible in the surface current map because they lay outside the
HFR field.

The zonal geostrophic velocity ug(y,z) computed from the
glider is mostly westward but reduced with respect to Transect 1 (T1) in
Fig. 3c, as expected during an upwelling episode. The difference between
geostrophic velocity in T1 and T3, considering also the elapsed time between
the two transects, is consistent with the estimate of the timescale
TW(Whitney and Garvine, 2005) of 2–3 days needed for wind events to
affect geostrophy in the NC (Piterbarg et al., 2014), and it suggests that E1
can modify stratification and geostrophic velocity after a sufficiently long
wind forcing period.

The change in ug(y,z) is quantified computing the
corresponding zonal transport (Fig. 8). For the integrated transport
computation, the 5 cm s−1 isotach was used to identify the Northern
Current, as done, e.g., by Albérola et al. (1995a) and Conan and Millot (1995). A very
strong variability is seen with respect to the first transect, with the
transport reduced by ≈50 % going from ≈1.15 Sv for T1
to 0.7–0.6 Sv for T2 and T3.

Finally, we provide a preliminary assessment of the surface deviation from
geostrophy (that will be further investigated in Sect. 5) by comparing the
magnitude of the zonal geostrophic velocity uSg from the glider
with the total velocity uS depicted by the radar along the
glider track (Fig. 9). During T2, the zonal radar total velocity is
significantly lower than the geostrophic one, while the meridional component
of the total velocity is almost double that of the zonal one. Results for T3
are qualitatively similar but incomplete because of the limited radar
coverage. The observed magnitude difference in the zonal component from
glider (geostrophic) and radar (total velocity) suggests that ageostrophic
processes play a non-negligible role at the sea surface for T2–T3.

Transects T4 and T5 (9–12 and 12–15 December, respectively) are
characterized by mostly calm wind conditions (Fig. 2a), except for the brief
westerly wind event (E2), occurring in between the two transects. Winds
during the calm period are mostly westerly, except for some strong direction
oscillations prevalent for lowest wind speed (below 4–5 m s−1),
mostly evident in the Porquerolles station records. During the last day of
T5, the onset of the third wind event (E3) occurs. Notice that E2 lasts less
than a day, which is significantly less than TW estimated by
Piterbarg et al. (2014), so that it is not expected to modify the
stratification and geostrophic velocity structure even though of course it
influences the surface velocity. The results of T4 and T5 are qualitatively
similar, and the T5 results are shown in Fig. 5.

The hydrographic transects (Fig. 5a, b) indicate a narrowing and steepening
of the frontal region characterized by warmer and fresher water in the
surface layer. This is shown also by the σ isopycnals in Fig. 7 that
are very similar for T4 and T5, and suggests a strong frontal area closer to
the coast, approximately north of 42.7∘ N.

The radar surface velocity (Fig. 5d) is very different from the previous
transects (Fig. 4d). The coverage is more extended and the velocity is almost
completely zonal, showing the typical westward structure of the Northern
Current. Notice that, even though the current actually deviates from the
zonal direction during E2 (as further discussed in Sect. 5), the
contribution to the average shown in Fig. 5d is very modest, because the
average is performed during the glider sampling that overlaps only for a few
hours with E2 (Fig. 2a). Also, E2 does not appear to significantly modify the
stratification, the geostrophic velocity and the associated transport, as
can be seen by the comparison of the two transects T4 and T5 in Figs. 7–8.
This is in keeping with the fact that the duration of E2 is shorter than
TW.

The surface comparison between geostrophic uSg and total velocity
uS from HF radar shows an excellent agreement in the zonal
direction for both T4 and T5 (Fig. 9c, d), while the meridional component in
the frontal region is significantly lower than the zonal one (approximately
70 % and 85 % for T4 and T5, respectively). Overall, the results
suggest that the current during these two transects is mostly zonal and
geostrophic even at the surface, i.e., sustained by the large-scale pressure
gradient that maintains the general and mesoscale circulation in the Ligurian
basin.

4.4 Transects 6: wind event E3

The last transect T6 (15–18 December) is dominated by the wind event E3,
that is mostly westerly but veering toward northerly during the last day. The
results are summarized in Fig. 6.

The hydrographic transects show a cooling of ≈1–1.5 ∘C in the frontal region, together with a strong
flattening of the isopycnals as shown also in Fig. 7. The surface velocity
depicted by the HF radar (Fig. 6d) is mostly meridional and offshore, in
agreement with a wind response leading to upwelling. The geostrophic
velocity is reduced (Fig. 6c), and the westward jet structure appears
fragmented in several recirculation cells (as discussed for T2 and T3). The
corresponding zonal geostrophic transport is reduced with respect to the
previous transects, and is even lower than for T3 and T4, reaching values of
≈0.45 Sv (Fig. 8). The comparison between surface geostrophic
uSg and radar-based total velocity uS (Fig. 9e)
shows a significant deviation from geostrophy at the surface, as expected.
uSg has a complex pattern, while uS is
dominated by the meridional component (≈30 % bigger than the zonal
velocities).

Overall, the results are qualitatively similar to the ones of T2 and T3,
describing an upwelling response to the wind that influences and weakens the
geostrophic circulation. It is interesting to notice, though, that there are
also some differences in the hydrographic properties with respect to the
previous transects that are likely to be related to the transition from
late-summer to winter conditions. The salinity minimum present in the first
transect (Fig. 3b) vanishes with time and it is almost absent in T6
(Fig. 6b), suggesting that the late summer conditions in T1 are turning
toward a more typical winter configuration, probably due to the recurring
effects of upwelling and mixing associated with the winter wind episodes.
This is also shown by the pycnocline deepening by ≈30 m in the
offshore central region (Fig. 7), occurring after the first two glider
transects.

4.5 Summary of results

The main results from the above analysis can be summarized as follows.

The observed variability of the Northern Current during the experiment
period is dominated by wind response. In addition to this synoptic variability,
the overall hydrographic conditions also suggest early stages of transition from late summer to fall–winter conditions.

In absence of strong winds, the current is mostly zonal and geostrophic
even at the sea surface. The associated zonal geostrophic transport over the
water column is of the order of 1 Sv.

The response to strong westerly wind events (higher than 10 m s−1
and lasting more than 2–3 days) induces offshore meridional currents at the
surface and an upwelling response in the water column that flattens
isopycnals in the frontal region. The westward zonal geostrophic current is
weakened, and the associated zonal transport decreases, up to 40–50 %,
reaching values of ≈0.7–0.5 Sv.

A strong wind event lasting less than 1 day does not modify stratification
and geostrophic velocity in the water column.

In Sect. 4, we have investigated the overall response of the NC to wind
forcing, quantifying the variability of the water column stratification and
of the zonal geostrophic transport. Here, we focus on the processes that
regulate sea surface currents' response to direct wind forcing. Our final goal
is to identify the ageostrophic wind-induced surface velocity
uSaW, and characterize it in terms of amplitude and angle
with respect to the wind.

The difficulty lies in the fact that the quantity that is actually measured
by HF radar is the total surface velocity uS, rather than
uSaW. This is a general problem in the study of surface
wind response. Information on uS is provided by several
instruments such as drifters, ADCP, or HF radar as in our case, and to
decompose it in its various components (Eq. 2) is not an easy task
(Rio and Hernandez, 2003). This is especially true in coastal studies where altimeter-based geostrophic velocities are not reliable. Often in experimental coastal
studies, the surface velocity uS is correlated with the
wind to investigate which percentage of the current variance can be explained
or studied at different scales, in order to decompose various processes
(Kim et al., 2010).

Here, we follow a two-step approach. As a first step, we consider the total
velocity uS measured by the HF radars, in order to obtain
some general information on the surface response to the westerly wind events.
In particular, we investigate the time evolution of the angle between the
current and the wind. As a second step, we isolate uSaW in
selected periods, where we can provide an estimate of uSg
based on the results of Sect. 4.

5.1 Investigation of the angle between wind and total surface velocity

Here, we characterize the wind response in terms of the angle between the
wind and the total surface currents uS as measured by the
radars. At each time interval of 1 h during the experiment period (Fig. 2a),
the angle α between the radar surface currents and the ALADIN winds is
computed for all the available radar grid points, interpolating the winds
over the radar grid. At each time step, α is spatially averaged and
time series of mean values and standard deviation (SD) are generated.

Results for the angle α¯(t) spatially averaged over the HFR
field at each time step and SD(t) are shown in Fig. 10, with
superimposed the time periods of the three wind events E1, E2, and E3
(Fig. 2). Positive (negative) values indicate currents to the left (right) of
the wind. During all wind events, α¯ is significantly negative,
except for a short period in 16 December, when a positive peak occurs. Notice
though that the wind during that day dropped below the 10 m s−1
threshold (Fig. 2b). When the wind is low, i.e., outside the event periods,
the angle oscillates between positive and negative values. Overall, the close
response of the surface currents to the identified wind events provides a
posteriori support to the choice of the 10 m s−1 wind speed threshold.

Figure 10Spatially averaged angle α¯(t) between total surface
currents uS and average ALADIN winds over the HFR coverage
(blue line). The black dashed line indicates a 0∘ angle. Negative
angles indicate currents to the right of the wind direction. The cyan lines
represent the SD. The limits of the selected wind events (E1, E2, and E3) are
indicated with red dashed lines (see Fig. 2b for more details).

The results suggest a strong response of the total surface velocity to the
wind events, with currents that tend to rotate to the right of the wind. The
variability, quantified by the SD, is high, even though mostly confined to
negative values. This indicates the presence of some inhomogeneity in the
wind response, as already evident in the radar averages of Figs. 4, 6. These
inhomogeneities can be due to many causes, from the configuration of the
coast and/or the bathymetry (Kim et al., 2009), to the presence of mesoscale or
submesoscale features, to inhomogeneities in the wind forcing over the radar
coverage. Even though the ALADIN local wind is mostly homogeneous in the area
of interest, wind gradients at larger spatial scales can also play a role in
the surface currents' response (Lebeaupin Brossier and Drobinski, 2009).

The average α¯(t) values are ≈-62.00∘ for E1,
≈-93∘ for E2, and ≈-56∘ for E3. Since the
wind is prevalently westerly (Fig. 2b), this suggests that the current is
prevalently moving offshore, in agreement with the results in Sect. 4.
Possible reasons for the differences between the three events will be further
discussed in Sect. 5.3. The magnitude of the correlation between wind and
total currents, as well as the phase angle between wind and currents, can
also be estimated through the complex correlation method introduced by
Kundu (1976). The phase angle estimated with this alternative method
(not shown) is comparable, within the SD range, to the time series in
Fig. 10. The average correlation magnitude between total currents and wind
has values around 0.4 during the three wind events, which is reasonable given
that total currents measured by HFR include the Ekman response to winds as
well as other surface processes not directly wind related.

We notice that the angle between the total velocity and the wind is not
directly indicative of wind response since uS contains also
the geostrophic and ageostrophic residual components, and therefore
α¯ cannot be compared with the angles predicted by the
theoretical Ekman-like uSaW solutions. In the following,
we will perform the decomposition of the geostrophic component from the HF
radar total currents to estimate the magnitude and angle of
uSaW.

5.2 Estimation of the geostrophic component and ageostrophic wind response

Here, we first of all assume that, during wind events, the ageostrophic
velocity is dominated by the wind-induced component, i.e.,
uSaW≫uSR. This is partially justified by
the fact that the uSR processes are mostly high frequency,
and oscillations from tides are typically small in the area
(Albérola et al., 1995b; Arabelos et al., 2011) while inertial oscillations are expected
to be weaker during winter. Also, we recall that, as discussed in Sect. 3.5,
we obtain consistent results using raw and 36 h low-pass-filtered HF radar
data. The geostrophic component uSg, on the other hand,
cannot be discarded since the results in Sect. 4 show that
uSg remains a sizable part of uS in all
cases (Fig. 9), even though its transport is reduced in presence of westerly
wind events (Fig. 8).

As discussed above, performing the decomposition between ageostrophic and
geostrophic components is challenging in most cases. In our case, we have
information on the geostrophic velocity from the glider transects, but it is
limited to the zonal direction and has restricted coverage in space and
time. The results in Sect. 4, though, indicate that at least in some
periods more extensive information can be obtained from the combination of
glider and HF radar results.

During Transects 4–5, i.e., during the period 9–15 December when the wind
was weak most of the time, the radar zonal velocity along the glider transect
is very similar to the geostrophic one while the meridional velocity is
reduced (Fig. 9c, d). The corresponding radar velocity field over the whole
region (Fig. 5d) shows a well-defined zonal current with weak meridional
dependence. These results justify an ansatz that, during periods of weak
winds, the geostrophic surface field uSg can be
approximated on the basis of the HF radar velocity appropriately averaged or
filtered. We also assume that this estimate, indicated as
uSg^, persists during wind episodes shorter than
the timescale TW, i.e., for episodes of the order of 1 day. This
is in agreement with the results in Sect. 4 regarding E2 (lasting less than
1 day) that suggest that the E2 winds do not significantly influence the
stratification and the geostrophic velocity.

This ansatz is used to perform the decomposition and to study the wind
response during E2. The geostrophic velocity uSg^
is estimated averaging the radar velocity over a time period T prior to the
onset of the wind event, and the ageostrophic wind response
uSaW is estimated subtracting
uSg^ from the total radar velocity
uS. A sensitivity study is carried out varying T in the
range of 6–12 h, and the rms difference between the results is ≈20 % for α¯(t).

An example of the geostrophic decomposition for a selected surface current
field during E2, on 12 December at 14:00 LT, is shown in Fig. 11. The estimated
uSg^ field, considering the basic case of T=6 h
for surface currents average, and the ALADIN wind are shown in Fig. 11a, c.
The HF radar total velocity uS is shown in Fig. 11b, while
the estimated uSaW, obtained subtracting the field in
Fig. 11a from the field in Fig. 11b, is shown in Fig. 11d. Superimposed
colors refer to the angle α of surface currents uSaW
with respect to the wind. Subtracting the zonal westward geostrophic
component from the total current field basically corresponds to rotating
currents eastward and it results in decreasing the angle with respect to the
westerly winds. The angle is negative for most of the field, except for a
few grid points in the northeastern corner of the radar field.

Figure 11Example maps of (a) 6 h time-averaged geostrophic flow
uSg derived from HFR prior to the wind onset,
(b) instaneous HFR surface currents uS during the
wind event, (c) ALADIN wind field, and (d) ageostrophic
surface currents uSaW superimposed on the color-coded map
quantifying the angle α between the ageostrophic component and ALADIN
wind. Negative values indicate current to the right of the wind.

Time series of spatially averaged results are shown in Fig. 12, for periods
within E2 (left panels) and E3 (right panels) wind events. The estimated
uSaW^ is characterized in terms of magnitude and
angle with respect to the wind (Fig. 12a) averaged over all the radar grid
points. Also, the percentage of negative angle values distributed over the
radar field is shown in Fig. 12c, as an additional measure of variability.
The angle between the wind and the ageostrophic component has a time average
value α(t)‾≈-28∘, while the magnitude of
the ageostrophic component reaches values of ≈25 cm s−1,
comparable to the average magnitude of the geostrophic component and
corresponding to the ≈2 % of the ALADIN wind average magnitude
(about 13 m s−1). Negative angles, i.e., ageostrophic component to the
right of the wind, prevail over the radar current field (up to about 80 %
of all grid points) during the wind event (Fig. 12c).

Figure 12(a, b) Time series of the spatially averaged ageostrophic
component uSaW^ magnitude (top panels) and angle
α(t) (middle panels) with respect to the wind direction (negative
angle indicates currents to the right of the wind). The cyan lines in the bottom
panels represent the SD. The black dashed lines in the top panels represent
the average magnitude of the geostrophic component
uSg^, while the black dashed lines in the middle
panels indicate 0∘ angles. (c, d) Time series of the
percentage of negative angles α (between ageostrophic component and
wind) distributed over the HFR coverage. The black dashed lines in the bottom
panels indicate 50 %.

The same method has also been applied to the onset of the wind event E3,
considering only the first day of the wind episode, when we can assume that
the estimate of the geostrophic velocity holds. Results in Fig. 12b show the
angle between the wind and the ageostrophic component, with time average
α(t)‾≈-26∘, while the ageostrophic component
magnitude reaches values of ≈30 cm s−1, comparable to the
average magnitude of the geostrophic component and corresponding to the
≈2.5 % of the ALADIN wind average magnitude (about
12 m s−1). Negative angles, i.e., ageostrophic component to the right
of the wind, prevail over the radar current field (up to about 90 % of all
grid points) during the wind event (Fig. 12d).

The surface current response to both wind events considered here shows
similarities in terms of the angle between the ageostrophic component and the
wind direction (about -25∘) and also considering the magnitude of
the ageostrophic component compared to wind speed (about 2 % as previously
observed by Chang et al., 2012 and Poulain et al., 2009). Surface currents
appear to respond to the wind quite homogeneously in space over the whole HF
radar field.

5.3 Discussion

The results in Sect. 5.1–5.2 show that the average angle between the
surface current and the wind is very different for the total surface current
uS (α¯≈-55 to -90∘) and for
the wind-driven ageostrophic component uSaW,
(α¯≈-25 to -30∘). This highlights the
importance of subtracting the geostrophic component of the velocity,
especially in a boundary current situation where it is very relevant. The
correction decreases the angle to the right of the wind, as it can be
expected since the geostrophic velocity is primarily zonal and westward while
the wind is mostly westerly.

More in detail, the different values of α¯ for
uS during the three wind events (Fig. 10) can be due to a
number of reasons. A first hypothesis is that they are linked to different
values of the geostrophic velocity uSg. From the results in
Sect. 4, uSg is expected to be stronger and more zonal
during E2 and at the beginning of E1 and E3, i.e., when the wind has not yet
acted to weaken it. This could explain the observed values of α¯≈-90∘ during those periods. As the time progresses during
wind events E1 and E3, the zonal geostrophic velocity weakens, and as a
consequence the angle is expected to decrease, as shown in Fig. 10. Another
possible reason for the variability in α¯ values is the presence
of time-varying inhomogeneities in the field, as suggested by the current
reversals in Fig. 4, that could be due to, for instance, the interaction with
the outflow from the Gulf of Lion (Schaeffer et al., 2011).

For uSaW, the values of α¯ are more similar in
the two cases considered and the variability is reduced. It is interesting to
compare these results with previous results in the literature, even though
the comparison is challenging due to the use of different data and methods. A
number of recent results are based on subtracting the geostrophic component
estimated from altimetry data, and they consistently show angles to the right
of the wind (in the Northern Hemisphere). Results from HF radar in the
Kuroshio area (Tokeshi et al., 2007) suggest values of ≈38–48∘, while results from SVP drifters with drogue at 15 m
(Rio and Hernandez, 2003) provide values of ≈10–40∘ at global scales
for latitudes higher than 30∘ N. In the Black Sea, SVP drifter
data (Stanichny et al., 2016) suggest values of ≈13∘ at the sea
surface. Finally, in the Mediterranean Sea, Poulain et al. (2009) find from SVP
and CODE drifters (drogued at 1 m) values of ≈27–42 and ≈17–20∘, respectively, obtained without subtracting the geostrophic
component. Overall, these values suggest a range of ≈10–40∘, that is consistent with our results. With respect to our
results, though, we notice that most of the previous results have been
obtained considering a larger-scale geostrophic component and longer
timescales of a few days. An exception is given by the work of
Sentchev et al. (2017) in the Toulon area, that considers daily wind
oscillations corresponding to light sea breeze. Results from HF radar and
ADCP in this case suggest angles of ≈15–20∘ to the left of
the wind, indicating a different balance with respect to the typical Ekman
balance.

An important final remark is the fact that, as pointed out in Sect. 3,
estimates of uSaW based on HF radars and surface drifters
are likely to be at least partially biased by the Stokes drift-like component
of the velocity (Ardhuin et al., 2009). This component is expected to be in the
same direction as the wind, therefore causing a bias that tends to decrease
the value of the estimated angle. In our case, then, the angle of the actual
Eulerian velocity could exceed -30∘. This issue, that is common
to all the works based on HF radar and surface drifters, is outside the scope
of the present paper but it will be considered in future works, considering
additional wave spectra information.

In this paper, a multi-platform observing system is used to monitor the
variability of the boundary current of the northwestern Mediterranean Sea,
i.e., the Northern Current. The adopted multi-platform system gives synoptic
measurements of currents and water masses' properties at spatiotemporal
scales that cannot be resolved only with classical vessel surveys or
satellite remote sensing. We use water column data from repeated glider
transects and vessel surveys, surface current fields from HF radar, wind time
series from a weather station, and an atmospheric model to describe the evolution of the NC off
Toulon for a period of approximately 2 weeks in December 2011.

The hydrographic transects display flattening of isopycnals and deepening of
the mixed layer offshore, evidencing early stages of the transition from late
summer to fall–winter typical conditions (Albérola et al., 1995a; Guibout, 1987).
In addition, the NC variability is dominated by a synoptic response to wind
events. When the wind is weak, the current is mostly zonal and in
geostrophic balance even at the surface, with a zonal transport associated
with the NC of ≈1 Sv. During two strong westerly wind events lasting
longer than 2–3 days, an upwelling response is observed, with offshore
surface transport, surface cooling, flattening of the isopycnals and reduced
zonal geostrophic transport (0.5–0.7 Sv). When the wind lasts less than
1 day, surface currents respond to winds but the water column
stratification and the geostrophic transport are not affected because the
wind event is not persistent enough.

We also specifically investigate the surface currents' response to the wind.
The total surface current as observed by the HF radar is found to respond to
the wind events, rotating at ≈-55 to -90∘ to the right
of the wind. During the first day of selected wind events, we also perform a
decomposition between geostrophic and ageostrophic components of the surface
current using results from glider and HF radar. The directly wind-driven
ageostrophic component is found to rotate by a smaller angle ≈-25 to
-30∘ to the right of the wind. The ageostrophic component
magnitude corresponds to ≈2 % of the wind speed.

This paper provides a first step in the joint use of glider and HF radar data
to describe the variability of a boundary current in terms of both
geostrophic and ageostrophic processes. Results show a high synoptic
variability of the geostrophic component related to wind episodes persistent
enough to modify water column stratification and pressure gradients, pointing
to the difficulties of decomposing flow dynamics according to timescales
and forcings (Kim et al., 2010).

The decomposition in geostrophic and ageostrophic velocity was carried out
for space and timescales smaller than in most previous works (Rio and Hernandez, 2003; Tokeshi et al., 2007), i.e., of the order of 1 day and tens of kilometers, as appropriate
scales for the Northern Current. Further developments in the decomposition
method are foreseen using time-dependent geostrophic velocities. This
approach will be first tested using models results with an Observing
System Simulation Experiment (OSSE) type of approach, and we expect that it will
provide useful insights for data assimilation and data blending applications.
Other methodologies involving other in situ data or remote sea surface temperature (SST) measurements
(Essen, 1995) can also be foreseen for the identification of the
geostrophic part of the flow.

A number of interesting issues, that are not considered here, will be
considered in future works. They include nonlinear wind response in the
frontal area, and interactions with mesoscale and submesoscale instabilities
that can modulate the geostrophic and ageostrophic response. Also, the
effects of the bias due to the Stokes-like term in the HF radar velocity
retrievals need further investigation.

More generally, several multi-platform observing systems are recently
developing as a transnational effort within the Mediterranean oceanographic
community. These systems are making available unprecedented synoptic
high-resolution datasets that could be combined not only for specific
scientific purposes but also for practical applications such as the
management of coastal and marine shared resources.

The analysis of the dataset has been supported and co-financed by the
JERICO-NEXT project. This project has received funding from the European
Union's Horizon 2020 research and innovation program under grant agreement
no. 654410. The multi-platform experiment has been carried out within the
TOSCA project, co-funded by the European Regional Development Fund in the
framework of the MED program. Wind data were kindly made available by
Météo-France. The authors wish to thank R/V Urania's crew that
made the experiment possible, the glider support team of DT-INSU, and
MIO's HF radar team.

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The Northern Current (NC) in the NW Mediterranean Sea is studied by HF radar, glider, vessel survey, wind station, and model. NC variability is dominated by synoptic response to wind events, studied decomposing geostrophic and ageostrophic surface components. The combination of autonomous observing platforms with classical marine surveys provides high-resolution datasets for scientific purposes and practical applications such as the management of marine resources in the Mediterranean Sea.

The Northern Current (NC) in the NW Mediterranean Sea is studied by HF radar, glider, vessel...